| group | Admits | Deposit1 | Deposit2 | TotalApps |
|---|---|---|---|---|
| Both | 144 | 0 | 3 | 144 |
| GPA Splitter | 44 | 0 | 30 | 418 |
| LSAT Splitter | 193 | 0 | 7 | 210 |
| Neither | 37 | 0 | 22 | 993 |
In partnership with the Office of Institutional Research, the below report gives a current outlook on the state of UGA Law School’s admissions pool. Please do not send without permission.
Median Outlook
As of the run of this report, this table gives an outlook of the current deposits and median by median subgroups. Targets are set at 169+/3.9+
All Applicants Credentials
The below scatterplot shows the distribution of all applicants and their incoming credentials. UGA Scholars are excluded from the scatterplot. In the legend you can single click to exclude that status or double click to isolate.
To see the distribution of all applicants you can switch to the Histogram
Show the code
hline <- function(y = 0, color = "black") {
list(
type = "line",
x0 = 0,
x1 = 1,
xref = "paper",
y0 = y,
y1 = y,
line = list(color = color)
)
}
vline <- function(x = 0, color = "black") {
list(
type = "line",
y0 = 0,
y1 = 1,
yref = "paper",
x0 = x,
x1 = x,
line = list(color = color)
)
}
fig<-filter(current_yr,LSAT >0 & !is.na(LSAT))%>%plot_ly(
type = 'scatter',
mode = 'markers',
x = ~LSAT,
y = ~GPA,
color = ~App_Status,
text = ~Name,
hovertemplate = paste(
"<b>%{text}</b><br><br>",
"%{yaxis.title.text}: %{y:.2f}<br>",
"%{xaxis.title.text}: %{x:.0f}<br>",
"<extra></extra>"
)
)%>% layout(shapes = list(hline(3.89),vline(168.5)))
figForecasting Applications
Forecast Residuals
The residual plot below measure the fit over time, you’ll see spikes where the applicants at that time period are more or less than the forecast would have anticipated.
residuals_f`geom_smooth()` using formula = 'y ~ x'
Forecast by LSAT bin
The below graphs are historical and forecasted amount of applicants for each LSAT group and Residency status.
fore_fTotal Forecast
ggplotly(fore_y)